Data Visualization for airplane accident 2008-2022


About the data

  • The data is extracted from from ICAO (International Civil Aviation Organization) API, occurred in the last 15 years (from Jan 2008 to May 2022).

  • Original ICAO API datasets link is available below. API key required, with 100 free calls available using a company email for subscription. Every accidents year dataset requires one different call (available in CSV or JSON format). https://applications.icao.int/dataservices/default.aspx

Interest

In 2022 March, there are a flight accident in China occurred on the route to my city, Guangzhou. Our whole city were so sad because of the tragedy. We can easily imagine that the love ones in the destination city were extremely sad. Therefore, I want to analyze the data to see what components leads to the flight accidents based on the public data, what we can avoid to get a safer trip. I selected the recent 15 year flight accident data intentionally.

Research questions (probably 1-3):
1. Which phases during the flight is the most easy to have accidents?
2. Where is the location is the most frequent to have flight accidents?
3. What kind of flight accident (e.g., operator, model, location) cause the most fatal number?

Audience

The data visualization is public to the visitors who decide to have a flight trip.

To answer the questions above, I have the following ideas: ## Preliminary Ideas

  • Some documentation that you have played with the course data (EDA)

  • Preliminary ideas (even hand sketches) of different visualizations

  • Identification of the intended audience for each visualization

  • Note you might consider displaying the same data/relations more than once, with each plot displayed for a different audience.

  • The intended message is to be communicated for each plot. The proposal can be up to 3 pages (single-spaced), including everything.

Data Visualization for airplane accident 2008-2022


About the data

  • The data is extracted from from ICAO (International Civil Aviation Organization) API, occurred in the last 15 years (from Jan 2008 to May 2022).

  • Original ICAO API datasets link is available below. API key required, with 100 free calls available using a company email for subscription. Every accidents year dataset requires one different call (available in CSV or JSON format). https://applications.icao.int/dataservices/default.aspx

Interest

In 2022 March, there are a flight accident in China occurred on the route to my city, Guangzhou. Our whole city were so sad because of the tragedy. We can easily imagine that the love ones in the destination city were extremely sad. Therefore, I want to analyze the data to see what components leads to the flight accidents based on the public data, what we can avoid to get a safer trip. I selected the recent 15 year flight accident data intentionally.

Research questions (probably 1-3):
1. Which phases during the flight is the most easy to have accidents?
2. Where is the location is the most frequent to have flight accidents?
3. What kind of flight accident (e.g., operator, model, location) cause the most fatal number?

Audience

The data visualization is public to the visitors who decide to have a flight trip.

To answer the questions above, I have the following ideas: ## Preliminary Ideas

  • Some documentation that you have played with the course data (EDA)

  • Preliminary ideas (even hand sketches) of different visualizations

  • Identification of the intended audience for each visualization

  • Note you might consider displaying the same data/relations more than once, with each plot displayed for a different audience.

  • The intended message is to be communicated for each plot. The proposal can be up to 3 pages (single-spaced), including everything.